code: def __init__(
      self,
      calibration_dataset: Dataset,
      quantizer: ORTQuantizer,
      model_path: str,
      qconfig: QuantizationConfig,
      calibration_params: Dict,
      node_exclusion: List[str],
  ):
      super().__init__(
          calibration_dataset=calibration_dataset,
          quantizer=quantizer,
          model_path=model_path,
          qconfig=qconfig,
          calibration_params=calibration_params,
          node_exclusion=node_exclusion,
      )
  
      # Remove the unnecessary columns of the calibration dataset before the calibration step
      self.calibration_dataset = (
          self.quantizer.clean_calibration_dataset(calibration_dataset)
      )
  
file_path: optimum/optimum/onnxruntime/runs/calibrator.py
imports: from typing import Dict, List
  from datasets import Dataset
  from ...runs_base import Calibrator
  from ..None import ORTQuantizer
  from ..configuration import AutoCalibrationConfig, QuantizationConfig
  from ..preprocessors import QuantizationPreprocessor
  from ..preprocessors.passes import ExcludeGeLUNodes, ExcludeLayerNormNodes, ExcludeNodeAfter, ExcludeNodeFollowedBy
label_desc: Use image node_id 1 to create a new OnnxRuntimeCalibrator object from inherited base classes: Calibrator with example: obj = OnnxRuntimeCalibrator(calibration_dataset, quantizer, model_path, qconfig, calibration_params, node_exclusion)